Radial temperature profiles for a large sample of galaxy clusters observed with XMM-Newton
By A. Leccardi, S. Molendi. 2008
155 citations recorded by the source corpus.
Aims. We measure radial temperature profiles as far out as possible for a sample of ≈ 50 hot, intermediate redshift galaxy clusters, selected from the XMM-Newton archive, keeping systematic errors under control. Methods. Our work is characterized by two major improvements. First, we used background modeling, rather than background subtraction, and the Cash statistic rather than the $\chi^2$. This method requires a careful characterization of all background components. Second, we assessed systematic effects in detail. We performed two groups of tests. Prior to the analysis, we made use of extensive simulations to quantify the impact of different spectral components on simulated spectra. After the analysis, we investigated how the measured temperature profile changes, when choosing different key parameters. Results. The mean temperature profile declines beyond 0.2 R 180 . For the first time, we provide an assessment of the source and the magnitude of systematic uncertainties. When comparing our profile with those obtained from hydrodynamic simulations, we find the slopes beyond ≈ 0.2 R 180 to be similar. Our mean profile is similar but somewhat flatter with respect to those obtained by previous observational works, possibly as a consequence of a different level of characterizing systematic effects. Conclusions. This work allows us to not only constrain cluster temperature profiles in outer regions with confidence, but also, from a more general point of view, to explore the limits of the current X-ray experiments (in particular XMM-Newton ) with respect to the analysis of low surface-brightness emission.
Subfields: Astronomy and Astrophysics
View Paper: https://www.semanticscholar.org/paper/3cdfc91bce11e05157bdbf597ef55e6fc96c0933
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Citations in the corpus
- Formation of Galaxy Clusters (2012, background): “3.10 Cluster formation and Thermodynamics of the Intra-cluster gas Figure 4 (from Leccardi & Molendi 2008) compares the observed temperature profiles of a sample of local clusters with results from simulations that include the SN feedback.”
- Lensing and x-ray mass estimates of clusters (simulations) (2012, result): “The radial coverage is comparable to recent observations, some of which extend beyond R500 (Neumann 2005; Ettori & Balestra 2009; Leccardi & Molendi 2008; Vikhlinin et al. 2009).”
- Simulating the effect of active galactic nuclei feedback on the metal enrichment of galaxy clusters (2009, methodology): “2R180, while beyond that radius profiles are consistent with being flat, withZF e ≃ 0.3ZF e,⊙ using the solar abundance value by Grevesse & Sauval (1998) (≃ 0.2 in units of the solar abundance by Anders & Grevesse (1989), as reportedby Leccardi & Molendi 2008a).”
- X-ray spectroscopy of the Virgo Cluster out to the virial radius (2011, background): “Therefore, this comparison, in the hard energy band where the number of source counts is negligible, is a good way to detect a significant residual soft proton contamination (see Leccardi & Molendi 2008).”
- Evidence for heavy-seed origin of early supermassive black holes from a z ≈ 10 X-ray quasar (2023, unknown): “We froze the previously known red-shift of the cluster to z = 0.308 and set an abundance of 0.3 solar 45 .”
- Total mass biases in X-ray galaxy clusters (2008, background): “…the largest accessible radius and r500 typically being the largest distance where the ICM temperature can be reliably estimated through X-ray observations (e.g. De Grandi & Molendi 2002; Piffaretti et al. 2005; Vikhlinin et al. 2005; Pratt et al. 2007; Snowden et al. 2008; Leccardi & Molendi 2008).”
- The cool-core bias in X-ray galaxy cluster samples - I. Method and application to HIFLUGCS (2010, methodology): “To minimize the instrumental background, we extracted images from the cleaned event lists in a narrow band (0.7-1.2 keV, Ettori et al. 2010), which excludes the prominent Al (∼ 1.5 keV) and Si (∼ 1.8 keV) background lines (Leccardi & Molendi 2008).”